RecursiveFactorization.jl
RecursiveFactorization.jl copied to clipboard
JuliaLinearAlgebra
This is based on https://github.com/julia-actions/julia-invalidations. Adding such checks came up in https://discourse.julialang.org/t/potential-performance-regressions-in-julia-1-8-for-special-un-precompiled-type-dispatches-and-how-to-fix-them/86359. I suggest to add this check here since this package is widely used as a dependency. See also...
The current test for determining the BLAS vendor is: ```julia blaslib = if VERSION ≥ v"1.7.0-beta2" config = BLAS.get_config().loaded_libs occursin("libmkl_rt", config[1].libname) ? :MKL : :OpenBLAS else BLAS.vendor() === :mkl ?...
`lu!`: `DivideError: integer division error` for Arrays of `ForwardDiff.Dual`s with large chunkSize
I am experiencing an error `DivideError: integer division error` when trying to apply `lu!` to a Matrix of `ForwardDiff.Dual`s with a large chunk size. After trying to reduce the problem...
The following example causes julia to quit silently on Windows 10 (but not on Windows Subsystem for Linux) if run with more than 1 thread. ```julia using RecursiveFactorization, LinearAlgebra num...
The `thread` argument in e.g. `lu` does not propagate to `schur_complement!` (which uses `@tturbo`), so the execution is still partially threaded when `thread=Val(false)`. Is that intended?
